迈向2030元宇宙世代数字人文之戏曲教育数字化战略建议

Towards 2030 Cross-generational Research of the Metaverse:The Strategic Proposal for Digital Humanities of Chinese Opera Education

以科技创新力辅助作为中华民族文化基因之戏曲的当代表达,意义重大。应用元宇宙相关产制技术如XR(VR/AR/MR)相关软硬件、容积撷取(Volumetric Capture)、动作撷取(Motion Capture)、立体全息影像(Holographic)等,可探索出优秀表演者的训练建构过程,从而辅助戏曲教育训练,亦将能够在教育、学习、创作、研究、产学合作等各方面,以更为全面的人、机、环境等统合性整体规划与设计达到数字文化新业态。该“戏曲教育数字化战略建议”基于以上相关研究而形成,乃艺术(戏曲)、教育(科技)、研究(实验)的跨领域结合,期望透过新兴科技来辅助戏曲人才的培植,提出迈向2030元宇宙世代戏曲艺术专业教育所需的指标性素养,以提升各戏曲剧种从业人员之展演能力与青年观众之欣赏能力,更期许能在两岸甚至全球中华文化范畴内,产生面向新世代的戏曲素养教育风潮。如此,一股如同文艺复兴时期跨领域范畴的新思维力量,将逐渐在人工智能云时代的大数据里演绎。

It is of great significance to assist the contemporary expression of Chinese opera,which is the cultural gene of the Chinese nation,with the power of scientific and technological innovation. Applying metaverse-related production technologies such as XR(VR/AR/MR) related software and hardware,volumetric capture,motion capture,and 3D holographic images,etc.,to explore the construction process of excellent performers,will assist in the Chinese opera education and training. This will also be able to achieve a new format of digital culture with a more comprehensive overall planning and design encompassing man, machine, environment, etc. in education, learning, creation,research,industry-university cooperation,etc. The " Strategic Proposal for Digitalization of Chinese Opera Education" was formed based on the above-mentioned related research. It is a cross-field combination of art(Chinese opera),education(technology),and research(experiment). The 2030 metaverse generation requires the index quality needed for the professional education of Chinese opera art in order to enhance the performance ability of practitioners of various opera types and the appreciation ability of young audiences. It is also expected to generate new generations of opera literacy education in the context of Chinese culture on both sides of the strait and even around the world. In this way,a new thinking force that is like the cross-field category of the Renaissance will gradually be interpreted in the big data of the artificial intelligence cloud era.